Topics in IoT: Wireless Sensing
- Course: CS 437 EKS - Fall 2023
- Instructor: Elahe Soltanaghai
- Time: Tuesday/Thursdays 2:00PM - 03:15PM Central
- Location: 1214 Siebel Center
- Office Hours: by appointment
- Course Syllabus: Here (Schedule is subject to change, check the most updated schedule here)
This course explores the foundations of smart wireless systems and wireless technologies for IoT through hands-on experimentation with real-world wireless devices. Students will perform bi-weekly projects in the IoT lab, building, analyzing, and evaluating WiFi-based (first half of the semester) and radar-based (second half of the semester) sensing solutions that are widely used in real-world applications (smart homes, IoT, self-driving cars, health monitoring, metaverse and mixed reality systems). This course will offer significant hands-on experience through semester-long projects, lab sessions, and overview of the commercial landscapes of the topics covered in class.
Pre-requisites
This class is open to undergraduate students only. It would be helpful if you have taken a class in computer networks, or embedded systems, as the class materials will be easier to access. If you are not sure about the prerequisites, please contact the instructor.
Keep in mind, this is an advanced course. Labs will have instructions of what you are supposed to do, but not step-by-step instructions of how you are supposed to do things. You are expected to use resources (Google, Stack Overflow, course staff, classmates, etc.) to figure out how to get things done.
Learning Goals of This Course
At the end of this class, students should be able to:
- Explain the basic operating principles and performance of the most-used technologies in mobile computing:
- Sensing and Actuation
- Networking Protocols
- Novel wireless technologies
- ML at the edge
- Energy harvesting
- WiFi-based sensing and localization
- Radar-based sensing and imaging
- Analyze a new wireless technology to extract key technical features and limitations. Specifically: infrastructure requirements, energy use, processing and timing demands, latency, and throughput.
- Assess how the physical-world constraints of an application scenario map to the capabilities of wireless communication and sensing technologies. Specifically: deployment area, device density, energy availability, spectrum access, and form factor.
- Design a smart system and estimate its performance given an application scenario.
Schedule 2023
(Schedule is subject to change, check the most updated schedule here)
| Week | Date | Day 1 | Date | Day 2 |
|---|---|---|---|---|
|
1 |
08/22 |
Getting Started |
08/24 |
What Makes "Things" Smart? Intro to embedded systems |
|
2 |
08/29 |
Everything Smart! Smart phones, homes, & beyond! |
08/31 |
Basics of Signal Processing intro to sensing modalities |
|
3 |
09/05 |
Lab 1-1 Raspberry Pi Programming |
09/07 |
Lab 1-2 Build a Smart Security Camera |
|
4 |
09/12 |
Wireless Networks |
09/14 |
Basics of Radios |
|
WiFi as a Sensor |
||||
|
5 |
09/19 |
Lab 2-1 From Smart to Spying Wireless Cameras |
09/21 |
Lab 2-2 Detect Hidden Spying Cameras |
|
6 |
09/26 |
Wireless Localization |
09/28 |
Wireless Sensing |
|
7 |
10/03 |
Lab 3-1 Localize Hidden Spying Cameras |
10/05 |
Lab 3-2 Build your Super SpyCam Finder |
|
8 |
10/10 |
Zero-power Platforms |
10/12 |
Hot Topics in WiFi Sensing |
|
9 |
10/17 |
Midterm Project Presentation |
10/19 |
Midterm Project Presentation |
|
Radar Sensing |
||||
|
10 |
10/24 |
Intro to Radars |
10/26 |
FMCW Radar Sensing |
|
11 |
10/31 |
Lab 4-1 Radar-based Motion Detection |
11/02 |
Lab 4-2 Keep your distance with radars! |
|
12 |
11/07 |
Radar Doppler/Phase Processing |
11/09 |
Hot Topics in Radar Sensing |
|
13 |
11/14 |
Lab 5-1 Radar-based Human Sensing |
11/16 |
Lab 5-2 Talk with a radar! |
|
14 |
11/21 |
Fall Break |
11/23 |
Fall Break |
|
15 |
11/28 |
Commercial landscape of Smart Wireless Systems |
11/30 |
Future of Wireless IoT! |
|
16 |
12/05 |
Final Project Demo |
12/07 |
Final Project Demo |
Projects (Fall 2023)
Localization Competition (Fall 2023)
Grading Algorithm:
- 50% Labs: pre-lab submission, lab attendance, and post-lab report
- 10% Mini-Quizzes
- 20% Midterm Project (Build a Spy Camera Finder)
- 20% Final Project (Build your magical radar sensing system)
Lab Hardware:
The required hardware for the labs will be provided to each group, so the students do not need to purchase any hardware. A big thank you to our industry sponsors, Bosch Research and Texas Instrument, for supporting the hardware kits for this class.
Anti-racism and Inclusivity Statement
The intent of this section is to raise student and instructor awareness of the ongoing threat of bias and racism and of the need to take personal responsibility in creating an inclusive learning environment.
The Grainger College of Engineering is committed to the creation of an anti-racist, inclusive community that welcomes diversity along a number of dimensions, including, but not limited to, race, ethnicity and national origins, gender and gender identity, sexuality, disability status, class, age, or religious beliefs. The College recognizes that we are learning together in the midst of the Black Lives Matter movement, that Black, Hispanic, and Indigenous voices and contributions have largely either been excluded from, or not recognized in, science and engineering, and that both overt racism and micro-aggressions threaten the well-being of our students and our university community.
The effectiveness of this course is dependent upon each of us to create a safe and encouraging learning environment that allows for the open exchange of ideas while also ensuring equitable opportunities and respect for all of us. Everyone is expected to help establish and maintain an environment where students, staff, and faculty can contribute without fear of personal ridicule, or intolerant or offensive language. If you witness or experience racism, discrimination, micro-aggressions, or other offensive behavior, you are encouraged to bring this to the attention of the course director if you feel comfortable. You can also report these behaviors to the Bias Assessment and Response Team (BART) (https://bart.illinois.edu/). Based on your report, BART members will follow up and reach out to students to make sure they have the support they need to be healthy and safe. If the reported behavior also violates university policy, staff in the Office for Student Conflict Resolution may respond as well and will take appropriate action.